Gopikrishnan Srikumar's Projects
Unsupervised Anomaly Detection System for Univariate Time Series
Badgers: Bad Data Generators
Deep Contrastive One-Class Time Series Anomaly Detection
A framework for easy running and evaluating your TSAD algorithm.
Must-read papers on graph neural networks (GNN)
GutenTAG is an extensible tool to generate time series datasets with and without anomalies; integrated with TimeEval.
A scikit-learn-compatible module for Isolation-based anomaly detection using nearest-neighbor ensembles
Python implementation of k-Shape
This is project made for one of the subjects at Warsaw University of Technology. Its aim is to detect anomaly in time series data.
Merlion: A Machine Learning Framework for Time Series Intelligence
This is an extension of NeuTraj, which accelerates the similarity computation of time series by neural metric learning
anomaly detection by one-class SVM
The application supports various anomaly detection algorithms, including Isolation Forest, One-Class SVM, DBSCAN, and KMeans clustering. Users can upload their time series data, select the appropriate algorithm, and receive visual and statistical insights into potential anomalies in their data.
š Elastic product quantization for time series
Symbolic Aggregate approXimation, HOT-SAX, and SAX-VSM implementation in Python
Collab with my great friend Mamba
Time series anomaly detection algorithm implementations for TimeEval (Docker-based)
Comparison of different algorithms for time series anomaly detection
Evaluation Tool for Anomaly Detection Algorithms on Time Series
TODS: An Automated Time-series Outlier Detection System
Time-Series Anomaly Detection Comprehensive Benchmark
Python implementation of SOTA methods for time series anomaly detection, methods such as DAMP variants, HOT SAX.
An End-to-End Benchmark Suite for Univariate Time-Series Anomaly Detection
R Functions implementing UCR Matrix Profile Algorithm
We propose a VAE-LSTM model as an unsupervised learning approach for anomaly detection in time series.